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Related Experiment Video

Updated: Jun 29, 2026

Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

Published on: February 23, 2020

Practice induces function-specific changes in brain activity.

Tamar R van Raalten¹, Nick F Ramsey, Jeff Duyn

¹Rudolf Magnus Institute of Neuroscience, Department of Neurology and Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands. t.vanraalten@umcutrecht.nl

|October 2, 2008

Summary

This summary is machine-generated.

Practice rapidly improves brain activity in encoding networks during automated tasks. Response selection networks show slower changes, indicating dynamic resource allocation for cognitive performance.

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Area of Science:

Cognitive Neuroscience
Neuroimaging

Background:

Practice significantly impacts performance and brain activity, particularly in automated tasks.
Automatization involves repeated information encoding with consistent responses.
The precise effects of practice on encoding and response selection remain unclear.

Purpose of the Study:

Investigate function-specific effects of automatization on brain activity.
Examine how practice influences encoding and response selection networks.
Understand the neural mechanisms underlying cognitive task automatization.

Main Methods:

Utilized a Sternberg task variant with m-sequences for optimized separation of encoding and response selection.
Employed a randomized event-related design for model-free Blood-oxygen-level-dependent (BOLD) signal measurement.
Measured brain activity across six practice runs and compared it to a novel task.

Main Results:

Observed immediate reductions in the cortical network for encoding after one practice run.
Detected less robust changes in the response selection network, appearing only after the third practice run.
Demonstrated heterogeneous decreases in brain activity across functional regions, not directly correlating with performance gains.

Conclusions:

Automatization leads to varied reductions in brain activity across different functional regions.
Cognitive performance relies on dynamic resource allocation within distributed neural networks.
Early increases in encoding efficiency may enhance capacity for managing interfering information, impacting complex cognitive tasks.